Key Takeaways
- A market cycle dashboard can be built from five freely available data series.
- Composite scoring transforms multiple metrics into a single cycle classification.
- The direction of change in the composite score is as important as its level.
- Quarterly updates ensure timely recognition of cycle transitions.
This hands-on lesson walks through constructing a market cycle dashboard for any metro area using freely available data. By the end, you will have a repeatable process for classifying any market's cycle position and tracking changes over time.
Step 1: Gather Quarterly Data
For your target metro, collect the following quarterly time series going back at least 5 years: (1) Zillow Home Value Index (ZHVI) from Zillow Research, (2) Zillow Observed Rent Index (ZORI) from Zillow Research, (3) Census Building Permits from the Building Permits Survey, (4) BLS Local Area Unemployment, and (5) Census Housing Vacancy Survey (quarterly, 75 largest metros). Compile these into a spreadsheet with consistent date formatting.
Step 2: Calculate Composite Score
Transform each metric into a directional signal: Price Momentum (ZHVI 12-month % change, scored -2 to +2), Rent Momentum (ZORI 12-month % change, scored -2 to +2), Supply Pressure (permits trailing 12-month as ratio to 5-year average, inverted so higher supply = lower score), Employment Strength (unemployment rate vs. 5-year average, lower = higher score), and Vacancy Direction (quarterly change in vacancy rate, declining = positive). Sum the five scores for a composite ranging from -10 to +10.
Step 3: Interpret and Act
The raw score alone is insufficient; the direction of change matters as much as the level. A score of +2 that is declining signals hyper-supply, while a score of -2 that is improving signals recovery. Plot your composite score over time and overlay it on a price chart to visualize how well the score leads cycle turns. Update quarterly and compare to your original classification.
Guided Practice: Building a Dashboard for Raleigh-Durham
You want to classify the Raleigh-Durham multifamily market as of Q3 2024.
- 1Gather data: ZHVI +5.1% YoY, ZORI +2.3% YoY, permits at 1.3x 5-year average, unemployment 3.4% (vs. 3.8% average), vacancy rising 0.3% QoQ.
- 2Score each: Price +2, Rent +1, Supply -0.6, Employment +1, Vacancy -1.
- 3Composite: +2.4, but declining from +4.1 two quarters ago.
- 4Classification: Late Expansion transitioning to Hyper-Supply.
- 5Action: avoid new acquisitions at current pricing; monitor for entry when score bottoms and begins rising.
Key Takeaways
- ✓A market cycle dashboard can be built from five freely available data series.
- ✓Composite scoring transforms multiple metrics into a single cycle classification.
- ✓The direction of change in the composite score is as important as its level.
- ✓Quarterly updates ensure timely recognition of cycle transitions.
Sources
- U.S. Census Bureau — Building Permits Survey(2025-03-15)
- CoStar Group — Market Analytics(2025-03-15)
Common Mistakes to Avoid
Building an overly complex dashboard with too many metrics.
Consequence: Information overload leads to analysis paralysis or missed signals buried in noise.
Correction: Limit to 8-12 core metrics organized into leading, coincident, and lagging categories.
Updating data inconsistently or mixing data vintages.
Consequence: Comparing Q1 vacancy to Q3 permits creates misleading cycle assessments.
Correction: Establish a regular quarterly update schedule and ensure all metrics reflect the same time period.
Test Your Knowledge
1.What is the most important design principle for a cycle dashboard?
2.Which is a leading indicator for real estate cycle turning points?
3.How should scoring thresholds in a cycle dashboard be calibrated?